Python 字典的遍历

# encoding: utf-8

test_dict = {  
    'attack': 379,  
    'attack_growth': 16.8,  
    'bp_size': 80,  
    'critical_rate': 0.15,  
    'ctype': '2',  
    'defense': 155,  
    'defense_growth': 8.25,  
    'exp_type': 'c',  
    'fate_id': ['ch_10004', 'ch_10005', 'ch_10006', 'ch_20003', 'ch_20004'],  
    'hp': 1861,  
    'hp_growth': 69.6,  
    'max_talent_lv': 7,  
    'name': 'caocao',  
    'pvp_skill_rate': 1,  
    'recover': 281,  
    'recover_growth': 11.8,  
    'souls_needed': 30,  
    'star': '5',  
    'talent_lv': 0,  
    'who_is': 'caocao',  
}  

# 不同的遍历方法
def test1():
    for key in test_dict:   # 这种最快, 其实也很显而易见
        pass

def test2():
    for key in test_dict.keys():  
        pass

def test3():
    for key, value in test_dict.items():  
        pass 

if __name__ == '__main__':  
    from timeit import Timer  
    t1 = Timer("test1()", "from __main__ import test1")  
    t2 = Timer("test2()", "from __main__ import test2")  
    t3 = Timer("test3()", "from __main__ import test3")
    # 执行100,000次的时间  
    print t1.timeit(100000)  
    print t2.timeit(100000)  
    print t3.timeit(100000)
    # 3次执行100,000次的时间  
    print t1.repeat(3, 100000)  
    print t2.repeat(3, 100000)  
    print t3.repeat(3, 100000) 

 结果:

0.0656280517578
0.0932841300964
0.217456817627
[0.06363296508789062, 0.062133073806762695, 0.0649728775024414]
[0.08316302299499512, 0.08275103569030762, 0.08605194091796875]
[0.21467804908752441, 0.19786405563354492, 0.20139288902282715]

 

 但空的循环没有意义

# encoding: utf-8

test_dict = {    
    'attack': 379,    
    'attack_growth': 16.8,    
    'bp_size': 80,    
    'critical_rate': 0.15,    
    'ctype': '2',    
    'defense': 155,    
    'defense_growth': 8.25,    
    'exp_type': 'c',    
    'fate_id': ['ch_10004', 'ch_10005', 'ch_10006', 'ch_20003', 'ch_20004'],    
    'hp': 1861,    
    'hp_growth': 69.6,    
    'max_talent_lv': 7,    
    'name': 'caocao',    
    'pvp_skill_rate': 1,    
    'recover': 281,    
    'recover_growth': 11.8,    
    'souls_needed': 30,    
    'star': '5',    
    'talent_lv': 0,    
    'who_is': 'caocao',    
}    
  
# 不同的遍历方法  
def test1():
    data = {}
    for key in test_dict:
        data[key] =  test_dict[key]
    return data

def test2():  
    data = {}
    for key in test_dict.keys(): 
        data[key] =  test_dict[key]   
    return data  
  
def test3():
    data = {} 
    for key, value in test_dict.items():    
        data[key] = value
    return data

print test1()
print test2()
print test3()
  
if __name__ == '__main__':    
    from timeit import Timer    
    t1 = Timer("test1()", "from __main__ import test1")    
    t2 = Timer("test2()", "from __main__ import test2")    
    t3 = Timer("test3()", "from __main__ import test3")  
    # 执行100,000次的时间    
    print t1.timeit(100000)    
    print t2.timeit(100000)    
    print t3.timeit(100000)  
    # 3次执行100,000次的时间    
    print t1.repeat(3, 100000)    
    print t2.repeat(3, 100000)    
    print t3.repeat(3, 100000) 

 

结果:

0.39611697197
0.423596143723
0.477458953857
[0.41298508644104004, 0.3765869140625, 0.3731379508972168]
[0.4185318946838379, 0.42104601860046387, 0.4249718189239502]
[0.42894506454467773, 0.4049968719482422, 0.3907771110534668]

差别没那么明显, 不同的遍历在不同地方处理数据